 Measuring dynamic economic effects under the constant-technology versus varying-technology assumptionsDennis P. Robinson and
Chung J. Liew
The Annals of Regional Science, 2001, vol. 35, issue 2, 299-331 Abstract: This study measures the time-period-specific industrial price and output effects of cost-related variables (transportation cost, wage rate, and interest rate) by utilizing the Dynamic Variable Input-Output (VIO) model. The Dynamic Variable Input-Output (VIO) model extends the static single regional version of the MultiRegional Variable Input-Output (MRVIO) model which is a partial general equilibrium model that incorporates the input-output model. By using the 15 sector industrial transaction table derived from the 1987 U.S. Benchmark input-output table for the constant-technology assumption case, and transaction tables derived from the 1987-1983 U.S. input-output tables for the varying-technology assumption case, we estimate cost-related variable effects on industrial price and output that are spread over several years. The dynamic price and output elasticities identify each period's impacts, and they add up to the static total price and output elasticities, respectively, when we adopt the constant-technology assumption. When we adopt the varying-technology assumption, each period's impacts do not add up to the neat dynamic totals. This study also finds that the initial period's price and output elasticities of the Dynamic VIO model are exactly the same as price and output elasticities of the static VIO model, thereby showing that the static VIO model underestimates the price and output impacts. Empirical results show that price elasticities are all positive for both own and cross impacts. Empirical results also show that output elasticities are negative for own impacts but mixed in sign for cross impacts because of the substituting behavior of firms and consumers. The distributions of both price and output elasticities reveal that ripple effects vary among different industries, over different time periods, among the cost-related variables, and between the two different technology assumptions. The distributions of both price and output impacts are more apparent during the first four or five periods. Hypotheses testings on the differences of mean elasticities between the two cases of technology assumptions show that under 10% level of significance, there are almost no differences in elasticities between the two cases of technology assumptions. However, as we increase the significance level, the total of five year periods' impacts show that they do differ under the two technology assumptions. Consequently, we recommend the use of constant technology for forecasting time horizons less than five years, and the use of varying-technology for forecasting time horizons longer than five years. JEL-codes: C61 C88 D57 D58 (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:anresc:v:35:y:2001:i:2:p:299-331 Ordering information: This journal article can be ordered from Access Statistics for this article The Annals of Regional Science is currently edited by Martin Andersson, E. Kim and Janet E. Kohlhase More articles in The Annals of Regional Science from Springer, Western Regional Science Association Contact information at EDIRC. |
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